Rationale and design of a large-scale, app-based study to identify cardiac arrhythmias using a smartwatch: The Apple Heart Study

Abstract

Background: Smartwatch and fitness band wearable consumer electronics can passively measure pulse rate from the wrist using photoplethysmography (PPG). Identification of pulse irregularity or variability from these data has the potential to identify atrial fibrillation or atrial flutter (AF, collectively). The rapidly expanding consumer base of these devices allows for detection of undiagnosed AF at scale.

Methods: The Apple Heart Study is a prospective, single arm pragmatic study that has enrolled 419,093 participants (NCT03335800). The primary objective is to measure the proportion of participants with an irregular pulse detected by the Apple Watch (Apple Inc, Cupertino, CA) with AF on subsequent ambulatory ECG patch monitoring. The secondary objectives are to: 1) characterize the concordance of pulse irregularity notification episodes from the Apple Watch with simultaneously recorded ambulatory ECGs; 2) estimate the rate of initial contact with a health care provider within 3 months after notification of pulse irregularity. The study is conducted virtually, with screening, consent and data collection performed electronically from within an accompanying smartphone app. Study visits are performed by telehealth study physicians via video chat through the app, and ambulatory ECG patches are mailed to the participants.

Conclusions: The results of this trial will provide initial evidence for the ability of a smartwatch algorithm to identify pulse irregularity and variability which may reflect previously unknown AF. The Apple Heart Study will help provide a foundation for how wearable technology can inform the clinical approach to AF identification and screening.

Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Figures

Figure 1

Study design. Overview of study flow with example tachograms and screenshots. The tachograms are not visualized or provided to the participant, and analyses are run in the background.

Figure 2

Participant study engagement screenshots. Number of days the participant has been in the study and total number of tachograms recorded for that participant as seen within the app on the phone (left) and watch (right).

Figure 3

Cumulative participant enrollment per week based on operational metrics. [1] Study launch with media promotion (Apple press release, App store feature). [2] Waiting room eliminated. All individuals that had been in the waiting room were invited into the study. Enrollment metering ceased. [3] Single recruitment email sent.